Case Study

GAIA Case Study

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CASE STUDY " Using Machine Learning to Generate Data-Driven Content Recommendations With its new architecture in place that leverages Qubole on AWS, job one at Gaia was to replace the legacy Postgres SQL rules- based recommendation engine with one that was quicker and easier to use, and that returned more relevant results. This new machine learning (ML) recommendation engine—based on Apache Spark and XGBoost models on Qubole—generates data-driven content suggestions to help subscribers decide which videos to watch next. In the eight months since the new engine went live, the results have been impressive. "We've seen a 50 percent lift in average minutes watched"—a critical viewer-engagement metric—says Gaia product data analyst Patrick Lawlor. "We would not have been able to do that before Qubole." In addition, subscriber engagement has significantly improved.. Qubole enabled us to use machine learning to provide much better recommendations than the legacy Postgres data warehouse SQL rule- based engine we used to have." Patrick Lawlor Product Data Analyst, Gaia Improved Analysis and Reporting for Data-Driven Decision-Making Before Gaia partnered with Qubole, its reports from available company data were incomplete and lacked the business insights needed for decision-making. This was due in part to a technology infrastructure that couldn't handle the workloads, as well as to a data architecture that was inadequate for drawing data from multiple sources. Qubole enables Gaia to easily query data from a variety of sources—including AWS data repositories and email, financial, and customer-service platforms—to surface critical business insights. So, "It's possible to dig not only one layer down, but three, four or five layers to see why our numbers are what they are," says Andrew Koblitz, senior manager of financial planning and analysis. There's not just more and different data at the company's disposal—more than 66 terabytes of it reside in the company's new data lake. There's better data. This is because Qubole facilitates the validation of data before it's used for reporting and analysis purposes. So, company leaders can make data-driven business decisions with greater confidence than ever before.

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